From evidence to impact: purposeful use of implementation science theories, models, and frameworks in genomics and precision health
Abstract
A growing number of genomics precision health applications are supported by robust evidence, yet their integration into routine clinical and population health practice remains slow, uneven, and inequitable. This article demonstrates how implementation science (IS) theories, models, and frameworks (TMFs) can support the translation of evidence-based genomics applications by presenting three cases from pediatric precision oncology, reproductive genetic carrier screening, and population genomic screening for hereditary conditions. Across the three cases, IS TMFs were purposefully selected, adapted, combined, or supplemented to fit the implementation context, core complexities, and the conceptual work required, and were revisited as implementation evolved. We argue that this purposeful approach can provide an operational backbone for integrating precision health innovations into real-world systems of care and help transform individual implementation efforts into transferable knowledge.
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BibTeX
@article{fariman2026from,
title = {{From evidence to impact: purposeful use of implementation science theories, models, and frameworks in genomics and precision health}},
author = {Soroush Fariman and Stephanie Best and Natalie Taylor and Megan C. Roberts},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1949272},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1949272},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - From evidence to impact: purposeful use of implementation science theories, models, and frameworks in genomics and precision health
AU - Soroush Fariman
AU - Stephanie Best
AU - Natalie Taylor
AU - Megan C. Roberts
PY - 2026
DA - 2026/10/30
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1949272
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1949272
AB - A growing number of genomics precision health applications are supported by robust evidence, yet their integration into routine clinical and population health practice remains slow, uneven, and inequitable. This article demonstrates how implementation science (IS) theories, models, and frameworks (TMFs) can support the translation of evidence-based genomics applications by presenting three cases from pediatric precision oncology, reproductive genetic carrier screening, and population genomic screening for hereditary conditions. Across the three cases, IS TMFs were purposefully selected, adapted, combined, or supplemented to fit the implementation context, core complexities, and the conceptual work required, and were revisited as implementation evolved. We argue that this purposeful approach can provide an operational backbone for integrating precision health innovations into real-world systems of care and help transform individual implementation efforts into transferable knowledge.
SN - 2296-2565
ER -